Opening article
FastRTC is a new real‑time communication library for Python that simplifies building audio and video AI applications. The library includes built‑in speech‑to‑text and text‑to‑speech functions, and supports integration with LLMs and other APIs. Users can also obtain a free phone number to connect to their stream via stream.fastphone, requiring a Hugging Face token and offering higher limits for PRO accounts.
In the last few months, many new real-time speech models have been released and entire companies have been founded around both open and closed source models. To name a few milestones:
Despite the explosion on the model and funding side, it's still difficult to build real-time AI applications that stream audio and video, especially in Python.
That's why we're excited to announce FastRTC , the real-time communication library for Python. The library is designed to make it super easy to build real-time audio and video AI applications entirely in Python!
In this blog post, we'll walk through the basics of FastRTC by building real-time audio applications. At the end, you'll understand the core features of FastRTC :
We'll start by building the "hello world" of real-time audio: echoing back what the user says. In FastRTC , this is as simple as:
The next level is to use an LLM to respond to the user. FastRTC comes with built-in speech-to-text and text-to-speech capabilities, so working with LLMs is really easy. Let's change our echo function accordingly:
By lowering the barrier to real‑time audio and video AI development, FastRTC could accelerate the creation of interactive AI applications and services.